|
|
Absolute deviation, 绝对离差; M2 \( F! {$ O! |6 g; A# o
Absolute number, 绝对数
. V8 J- {. |- G& P* BAbsolute residuals, 绝对残差6 {0 e; ^1 N; ^0 z) g a+ T
Acceleration array, 加速度立体阵6 I1 ]0 ~$ r* L$ g/ }
Acceleration in an arbitrary direction, 任意方向上的加速度
/ z% x$ j* L3 h: y! F: |Acceleration normal, 法向加速度* ^1 f; K ]. H4 x6 b" q+ w( `. l6 L1 C
Acceleration space dimension, 加速度空间的维数5 V6 e$ b; R3 U, N, r4 `+ L
Acceleration tangential, 切向加速度/ z7 ~% _" e" A/ v
Acceleration vector, 加速度向量
% N- Q' ^% k4 r- b) K; {Acceptable hypothesis, 可接受假设+ S* [0 } R$ E. c1 H
Accumulation, 累积2 e% H" |* L% D+ }- A9 d1 c9 p
Accuracy, 准确度" X& F( h( ~' q: s4 T3 t, _' m
Actual frequency, 实际频数; S# N' ^ ^* m, A) H0 ]7 D' N, s
Adaptive estimator, 自适应估计量
. ^: |' j" n2 F0 _3 h+ }Addition, 相加1 C t5 K# j0 E7 U
Addition theorem, 加法定理
6 N, S4 {- G! g7 E0 {7 }Additivity, 可加性
0 I: Q- j6 A% `2 xAdjusted rate, 调整率 V# e2 f( X6 b% n1 P
Adjusted value, 校正值: L8 n% W* c5 L, U. I/ F1 U5 E" x
Admissible error, 容许误差
) L( l5 a! e) S1 y3 D' c' l) V# eAggregation, 聚集性
! t% j2 E: ^ m4 o2 H" X4 p: WAlternative hypothesis, 备择假设
, D" H" I8 A; K. F# b) u- K7 {Among groups, 组间
3 C4 c @ V9 lAmounts, 总量
" ~, Y. q- E B* [* KAnalysis of correlation, 相关分析
5 c4 s+ r4 S/ z3 ?1 K% pAnalysis of covariance, 协方差分析
- g) n, y( a( p1 C4 r$ CAnalysis of regression, 回归分析 K, r6 r( G6 c: X2 y
Analysis of time series, 时间序列分析
6 p K! z, U6 T/ FAnalysis of variance, 方差分析; }/ K3 d8 B w# O$ r$ j: x
Angular transformation, 角转换 w7 V7 F7 d4 t: H+ I
ANOVA （analysis of variance）, 方差分析3 p5 ]3 I5 R& `. v
ANOVA Models, 方差分析模型 l% }/ U4 }( _# E. U9 `
Arcing, 弧/弧旋% U" T. y* Y; U
Arcsine transformation, 反正弦变换# u) |' s @5 E" Y# w+ O6 C
Area under the curve, 曲线面积
1 t7 E, M1 p' H+ C! |; O/ kAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ' Z- ^9 j0 c( I2 q O$ R$ j
ARIMA, 季节和非季节性单变量模型的极大似然估计
1 e+ n# e! k; M* {9 t) c' nArithmetic grid paper, 算术格纸
+ K/ r+ j8 A9 a, XArithmetic mean, 算术平均数. v1 P( N U3 ]2 `7 t
Arrhenius relation, 艾恩尼斯关系8 }( f. ]; x7 r# N: C5 m' Y: |
Assessing fit, 拟合的评估" ?1 }% U3 G! {- ~1 J( t- b7 r
Associative laws, 结合律
- U/ ~+ _% G9 fAsymmetric distribution, 非对称分布 t* [7 @$ N y) v2 h
Asymptotic bias, 渐近偏倚
/ p$ K3 n# F3 Q0 |) ?6 j( B9 EAsymptotic efficiency, 渐近效率1 V/ t8 l( S! h
Asymptotic variance, 渐近方差
7 ]- \0 J6 j, KAttributable risk, 归因危险度
* J2 O0 y/ B4 O& b3 C- IAttribute data, 属性资料
- v' `# F4 t) o6 gAttribution, 属性
; e" B! f& I' h' h' |5 o0 [& EAutocorrelation, 自相关- z; v" l. N6 V% E/ r: p% z' C( ]1 K
Autocorrelation of residuals, 残差的自相关$ z, c$ f! K4 X: e
Average, 平均数8 } d' `3 q: d' ?9 S5 J: Y
Average confidence interval length, 平均置信区间长度
- t5 j# _) c! A2 b. h, GAverage growth rate, 平均增长率6 {9 }6 f" B9 w$ P- R6 k5 I
Bar chart, 条形图
: {4 L, O. Z* Y$ }Bar graph, 条形图2 B, D0 E# Y. p- k
Base period, 基期 h2 e. ~1 n" |) Q: ^! p
Bayes' theorem , Bayes定理
1 G( n; t" [8 L! P$ MBell-shaped curve, 钟形曲线
) Q' @5 D$ G. v. {! p# ]/ ~Bernoulli distribution, 伯努力分布6 Y) j/ \' R( K) h- h1 u
Best-trim estimator, 最好切尾估计量
7 i( b3 Q. q% Z. k8 o% z7 mBias, 偏性
: y8 B8 p+ d$ E9 P/ Z; l: T& NBinary logistic regression, 二元逻辑斯蒂回归, T0 u6 @$ |' P- o. z% v; y V
Binomial distribution, 二项分布* j( H7 P& ^7 s* D3 K! G. f1 D5 c, u
Bisquare, 双平方
/ w3 L% ?( o4 ~/ O% q2 oBivariate Correlate, 二变量相关
3 ]1 t2 j& W. e/ L, l9 A# B) WBivariate normal distribution, 双变量正态分布7 y# @( j( B+ q; A: c0 c* S" D
Bivariate normal population, 双变量正态总体
. `( t8 N D( E, D# }0 P0 |Biweight interval, 双权区间
/ x, w) u* Q' T+ w, TBiweight M-estimator, 双权M估计量7 p; g7 D) g# }$ d) l
Block, 区组/配伍组0 Q1 C8 T( r7 x3 w$ m7 p5 ~9 {
BMDP(Biomedical computer programs), BMDP统计软件包+ ]6 P" g, r. r |0 @/ _
Boxplots, 箱线图/箱尾图' A% Y8 `: s+ F/ ]+ Z( F7 _
Breakdown bound, 崩溃界/崩溃点; Q( b5 K3 v& q; }
Canonical correlation, 典型相关
* G$ f/ y% }& X. jCaption, 纵标目
" o8 e) }9 B/ }6 YCase-control study, 病例对照研究# Z" R$ z* \! ^0 k
Categorical variable, 分类变量
8 U9 r( W f+ G$ l( QCatenary, 悬链线0 \) T. v% p8 b1 ?- W: \
Cauchy distribution, 柯西分布
. o& V- D- q, oCause-and-effect relationship, 因果关系
+ t/ [$ _( ?2 ~5 X) XCell, 单元/ w6 v% m G6 o4 c
Censoring, 终检- I j. q0 O H. z- R# Y
Center of symmetry, 对称中心
) ^* `$ f$ A3 \Centering and scaling, 中心化和定标# L9 G5 V( X$ m
Central tendency, 集中趋势0 ?6 a1 ^: m6 v* H2 |9 E. H
Central value, 中心值7 o# j b s( G+ P/ o% e
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
' V: _- r) X+ b! E. @Chance, 机遇
' K, F9 q* q8 l- E2 p0 T6 LChance error, 随机误差! \( P5 w* V' {: A' i/ p( o) j
Chance variable, 随机变量
7 d3 k r% P- G) @8 ?( X4 KCharacteristic equation, 特征方程
5 M {5 k9 n, i, x& x9 sCharacteristic root, 特征根
8 `, i) x6 \* H( f6 t7 S9 B- x; yCharacteristic vector, 特征向量- e4 S9 `0 @* W' [, ~
Chebshev criterion of fit, 拟合的切比雪夫准则( P7 k' G9 I2 Q6 p8 \, x
Chernoff faces, 切尔诺夫脸谱图
0 y3 K! V! {+ D0 }! D( bChi-square test, 卡方检验/χ2检验
( N& u# m0 J0 I. c- d1 V0 XCholeskey decomposition, 乔洛斯基分解
( o) ~6 c$ f8 z9 W. c- n. X/ NCircle chart, 圆图 2 i, t( v3 o$ t3 Q( B
Class interval, 组距
1 T( ^5 |" I4 M7 v- Z- H9 v1 J. gClass mid-value, 组中值
/ h' K( f( v% F: ]' H7 vClass upper limit, 组上限 G5 C0 h5 V! j
Classified variable, 分类变量$ P" E% r8 N) _2 ]- H) ?: I* O
Cluster analysis, 聚类分析* Y9 J) {( q3 m
Cluster sampling, 整群抽样
! s3 f$ S* B6 Q9 {* K$ y, VCode, 代码
7 t4 K( E9 ~9 I% P! [Coded data, 编码数据, f; v6 D* W+ }- @3 F% Y& l! D, u( s
Coding, 编码9 v4 J9 _- u7 J) q% W2 o
Coefficient of contingency, 列联系数. u* U$ U1 L7 m
Coefficient of determination, 决定系数
; T, X4 u+ l5 ZCoefficient of multiple correlation, 多重相关系数1 t. r- ~+ M& ^+ k
Coefficient of partial correlation, 偏相关系数0 I2 ?. G% w) x: ~- M
Coefficient of production-moment correlation, 积差相关系数: W$ s; d; @ K
Coefficient of rank correlation, 等级相关系数0 V: ^, f6 f" m# K; g
Coefficient of regression, 回归系数
* ~) { r \" W. wCoefficient of skewness, 偏度系数$ _+ I9 L2 c% P' a
Coefficient of variation, 变异系数
% H' X! T2 Q7 j0 J3 WCohort study, 队列研究
: k. ]$ G# o9 V! C" A5 { h5 HColumn, 列
" o6 S% r2 p. i! M8 r" A$ O+ i# zColumn effect, 列效应% X7 ?" {( i3 w7 O0 A# f5 }" o
Column factor, 列因素, }3 U6 l0 _9 |' A0 f- I8 O1 Z
Combination pool, 合并
8 h$ c6 |" m" B- G- k% @* bCombinative table, 组合表; H2 H$ m/ B3 N# X! O8 ~1 ~( X1 v U W
Common factor, 共性因子) ^/ d5 W. K$ r0 f* I, p
Common regression coefficient, 公共回归系数' n, U, r/ D* Y$ v: x) Z
Common value, 共同值3 @# E' f! v3 v! u3 p" E
Common variance, 公共方差
& Z( E9 c$ L+ j, aCommon variation, 公共变异 h4 l. q$ f6 E. W! {
Communality variance, 共性方差, U- U. r8 a7 X {/ @
Comparability, 可比性
! f/ W7 x3 X ^: K! oComparison of bathes, 批比较 t: U# f4 O% ~; n K' b1 g& i% z6 j
Comparison value, 比较值& b" x k8 C+ }. a* ^' V# Y
Compartment model, 分部模型; R$ O, r/ }% v( u R8 _ w
Compassion, 伸缩+ Y' D4 H: H! p
Complement of an event, 补事件
8 T& ^/ w) L) X: F- W3 N- ?& {9 r& gComplete association, 完全正相关
# f( j6 a6 }3 G. j, v1 ^5 [% WComplete dissociation, 完全不相关
, `* \+ x; v, b0 G9 ^3 NComplete statistics, 完备统计量0 O3 Z" L4 Z: z* ^& W7 G
Completely randomized design, 完全随机化设计" Z) ]9 {& B5 g: n
Composite event, 联合事件1 M2 O- `8 l; y, ^
Composite events, 复合事件
, R7 B& o" x& WConcavity, 凹性5 o$ J7 _, f; h9 y$ x, [
Conditional expectation, 条件期望
' N& d3 j. {1 T3 Z: i: qConditional likelihood, 条件似然
9 ^/ \0 D* ^7 V& Z& y" SConditional probability, 条件概率
) `3 k" {) B$ N" zConditionally linear, 依条件线性+ y' s- A8 R1 D9 D+ y X
Confidence interval, 置信区间+ F& w9 I3 {9 E
Confidence limit, 置信限
' [8 ~: c5 I) c% ]8 O D8 { A5 _! VConfidence lower limit, 置信下限
c1 D2 {1 I! t+ dConfidence upper limit, 置信上限 e2 l$ z; ~$ g' f. `1 F' s) E
Confirmatory Factor Analysis , 验证性因子分析
# K) t3 s% w1 f+ mConfirmatory research, 证实性实验研究
! z) k* X4 a: _' u+ }5 L/ B. bConfounding factor, 混杂因素* m' j7 u$ L+ i$ `9 x
Conjoint, 联合分析! F9 ~! A% |6 v
Consistency, 相合性% {4 G+ X+ e( l: ~6 N4 I
Consistency check, 一致性检验, P$ A; {/ g+ Z" ^5 S, V6 d+ N
Consistent asymptotically normal estimate, 相合渐近正态估计: z" `3 M4 Y' K& W& ]4 t" W4 h7 [
Consistent estimate, 相合估计6 o1 ?+ e7 ~/ p) S9 v
Constrained nonlinear regression, 受约束非线性回归) i3 D, n+ }- t$ ~- X
Constraint, 约束% G, `# L) z. N' j
Contaminated distribution, 污染分布
9 ? m+ I+ A9 p( Y B EContaminated Gausssian, 污染高斯分布
5 k, b9 n. [+ s2 U4 S9 s6 `1 GContaminated normal distribution, 污染正态分布
7 [9 h3 { I0 g) l* t! }+ y/ iContamination, 污染
* X0 s% P+ f nContamination model, 污染模型
. P1 w0 K9 @) l- L% r8 K# t# o. hContingency table, 列联表
7 |2 ]7 C4 g) q; l8 _) ?# _Contour, 边界线: @$ n; c/ O6 @* A
Contribution rate, 贡献率+ ^: @' o8 T4 U- X
Control, 对照
8 h, y3 [" P5 i3 `: W7 nControlled experiments, 对照实验' r5 a7 k9 T v
Conventional depth, 常规深度
+ Y; ^% ?1 x0 JConvolution, 卷积9 o! c) ?, m1 s+ ], t
Corrected factor, 校正因子; B. U. |- `- s3 B& X
Corrected mean, 校正均值
4 i- r( U! h) _& p2 pCorrection coefficient, 校正系数; ]0 X) r+ o: s" |- z
Correctness, 正确性
" M% O- Q& Q: | q# e, C! F7 ICorrelation coefficient, 相关系数! g9 a4 v% q$ C* E/ l
Correlation index, 相关指数
8 ^" w3 v1 @- m0 U9 ZCorrespondence, 对应' D5 n5 a' r* X9 w! H' Y6 w! j
Counting, 计数
5 Z; x4 L& f& z$ {Counts, 计数/频数
5 ]2 j, p7 E& m' c2 N. [Covariance, 协方差$ S8 G7 U+ ?/ }$ c: U
Covariant, 共变
" Z% M @; b" |: j2 e: X& D" WCox Regression, Cox回归+ X: N* ]& v- B, U
Criteria for fitting, 拟合准则
! M% T t9 r) N3 E* p; OCriteria of least squares, 最小二乘准则
2 O; E; f1 j0 B. t* Z( CCritical ratio, 临界比6 r) f6 T8 g" H
Critical region, 拒绝域+ h$ L P }' M% M) M: n" y
Critical value, 临界值# u( k- d; t$ k) D
Cross-over design, 交叉设计
k" ?3 G1 G; q# OCross-section analysis, 横断面分析
1 z8 R' c/ x( m. }6 U; @" jCross-section survey, 横断面调查
8 r4 I6 p7 j! |0 ^9 ~" ]/ g9 ZCrosstabs , 交叉表
& X# t5 d: t% H9 g# p- vCross-tabulation table, 复合表
% K: S. e7 U/ |- q$ T2 G: JCube root, 立方根
5 c4 p: t# w8 f+ l( e m. {% L5 \% M2 cCumulative distribution function, 分布函数/ j9 D; I& {# y) u4 O9 g( R6 U
Cumulative probability, 累计概率& ^9 G& B% }. f H
Curvature, 曲率/弯曲
- X. j7 `( ]; ]3 F# A, u5 u9 S4 ^4 pCurvature, 曲率 R' `% o! |$ n# t
Curve fit , 曲线拟和 , ?; ~7 Z5 U* u8 E8 V" @9 p* |7 R
Curve fitting, 曲线拟合6 z" @/ ?, B8 a
Curvilinear regression, 曲线回归+ s' ~$ C# a4 t3 }( P
Curvilinear relation, 曲线关系$ Z* W9 p8 c' ?$ ?3 R
Cut-and-try method, 尝试法
6 U0 E' Z9 _. ICycle, 周期
: Z4 K. g" v0 @" y% ^1 X- o0 QCyclist, 周期性4 O+ P- S; a9 Y# u' E& j
D test, D检验4 G% F$ o+ [' `% e. T$ @
Data acquisition, 资料收集
- E/ r( ~1 N4 a! ~8 [ C1 S& m, qData bank, 数据库1 ]3 ^7 C8 Z; `6 O C5 e4 M
Data capacity, 数据容量
/ Y0 G0 A a4 X" \% x4 f- U. D0 yData deficiencies, 数据缺乏+ G) H& f+ w3 K# C' h. O1 q
Data handling, 数据处理
) I* t. E/ ]7 N9 I* |: vData manipulation, 数据处理
. O4 j& L& ^* J/ y5 C6 ^( i7 W. EData processing, 数据处理
. l& I1 J, P" ~$ l) g: ?: IData reduction, 数据缩减
8 k$ R3 x/ Q p5 }/ C! p/ p9 DData set, 数据集
! l4 m6 S( E6 t s9 @4 wData sources, 数据来源* z8 G1 @: h+ h% I2 ^$ [
Data transformation, 数据变换
/ C- A# y, l8 a0 C5 gData validity, 数据有效性
; H' I0 e% { e6 v& dData-in, 数据输入" T8 L3 r' W" W6 X8 D
Data-out, 数据输出
6 R1 x9 V& c4 e$ ^) w6 y! gDead time, 停滞期8 f" ~& H3 I E( T/ v
Degree of freedom, 自由度
5 d) p4 T Z" V! e, [8 k1 ]1 \8 JDegree of precision, 精密度. @5 w& E- c: M
Degree of reliability, 可靠性程度
; F; [3 O4 e0 z% M3 Q; |Degression, 递减1 {; }" n9 i9 B- s$ s. B/ ^) w
Density function, 密度函数5 {+ [1 b7 ^6 B6 O
Density of data points, 数据点的密度
% m2 c% y# I! u% `Dependent variable, 应变量/依变量/因变量4 E" y! i: a; J/ U
Dependent variable, 因变量
& i/ W O9 G- s) `Depth, 深度+ j! e; M, a1 @5 C# U
Derivative matrix, 导数矩阵
) Q" G' g( u+ v$ [8 mDerivative-free methods, 无导数方法% n, Q7 v0 L( v- P* K$ I
Design, 设计& n7 D) s% X' Y. p' q
Determinacy, 确定性1 v7 k4 ^8 u( j8 \2 w
Determinant, 行列式
% C) _/ y9 @1 ?3 Q+ HDeterminant, 决定因素
8 T# [$ s, p) [0 ~/ ZDeviation, 离差
/ f7 f1 l: |. O' D- b0 \1 x3 ^3 V+ W; b8 ?Deviation from average, 离均差
: `; I" @- \6 K: T6 o8 ^; t4 hDiagnostic plot, 诊断图, {2 |! a) m, R1 l7 m* n
Dichotomous variable, 二分变量
4 m7 E+ |7 J7 z% R, ~ r( J# U& t6 cDifferential equation, 微分方程
9 @4 K) V$ }/ u- L- ^" HDirect standardization, 直接标准化法
/ z& T y" y+ a7 z- f# gDiscrete variable, 离散型变量
' F1 v( f; p1 H" {DISCRIMINANT, 判断
2 F7 P0 \0 O) @Discriminant analysis, 判别分析
" ?2 Y6 U/ H1 _Discriminant coefficient, 判别系数- l" _/ r' ?/ b$ q" T
Discriminant function, 判别值
8 S% H1 X/ I. s% }; ? B0 K! zDispersion, 散布/分散度
3 H# }2 K% ?" N8 QDisproportional, 不成比例的! X8 D! K* V6 u, c! U% Q
Disproportionate sub-class numbers, 不成比例次级组含量- |& y. E( G+ p7 W5 z: o7 @8 a
Distribution free, 分布无关性/免分布# m! n0 S& z+ W5 o; {
Distribution shape, 分布形状( x+ w8 ?/ u( k* u1 e; d- C u" m! H
Distribution-free method, 任意分布法3 v% Z/ x! |* @6 o6 t6 `8 F2 W
Distributive laws, 分配律
$ n) a) W' q$ F. J+ R: XDisturbance, 随机扰动项7 M; P- n# {1 i0 P
Dose response curve, 剂量反应曲线
3 z9 N+ h7 _3 E& g8 f! l* v/ oDouble blind method, 双盲法
7 x D) ?: D/ ]Double blind trial, 双盲试验3 T. q2 f0 K% t- |6 ^; _5 u
Double exponential distribution, 双指数分布* E' h1 b# e+ t/ b* p) ]1 N
Double logarithmic, 双对数
* j- _4 X/ b5 g F2 ~Downward rank, 降秩
( O( H% E- ~* g; K3 p3 P" MDual-space plot, 对偶空间图
/ b* M/ W' e, e$ N7 wDUD, 无导数方法2 e% }7 C/ \% Z: U
Duncan's new multiple range method, 新复极差法/Duncan新法
+ Q% j- |; R* K4 hEffect, 实验效应
* o7 l/ C1 ^/ f, DEigenvalue, 特征值 }' e: {3 }' c) m# X0 w
Eigenvector, 特征向量
0 x$ \+ A" u/ [! M/ [9 ~9 TEllipse, 椭圆
" G H! b& n6 G* w9 Z( QEmpirical distribution, 经验分布
% C! {1 ?. D) I3 A2 gEmpirical probability, 经验概率单位
7 W9 p' k9 o, |3 KEnumeration data, 计数资料
8 v5 {( b6 m6 n5 N; UEqual sun-class number, 相等次级组含量6 r* d, _& O/ P% P5 b& U
Equally likely, 等可能! [, h$ T7 o6 t, U
Equivariance, 同变性
# q/ o$ h# e, e# D$ Z" dError, 误差/错误4 Q& j4 N2 J6 v0 c3 T
Error of estimate, 估计误差( ~/ U. H! H3 q. d% t M
Error type I, 第一类错误
9 E1 E( ^& d" R7 ^Error type II, 第二类错误+ H& V" Y' R9 k. z2 V; T" |, u+ Y" M
Estimand, 被估量
& I# j* x/ Y3 {/ Z: U+ Z' o m* u4 hEstimated error mean squares, 估计误差均方% L1 n1 c0 R( w( A& }1 P# m
Estimated error sum of squares, 估计误差平方和
& {0 S: `4 G$ }2 r1 O- fEuclidean distance, 欧式距离0 h+ E7 R- a' y" _
Event, 事件
* Q/ ]5 p% a$ {, p4 T4 G9 pEvent, 事件
# j# B, {3 J- ~9 C J vExceptional data point, 异常数据点9 n2 [# Z8 L1 `2 j1 c
Expectation plane, 期望平面# q$ e! f, T0 w. U, v; `: w$ B
Expectation surface, 期望曲面& H" G8 \9 x6 U% \
Expected values, 期望值2 a! I5 B- R0 Y+ P- O5 [
Experiment, 实验, y7 L* s& D; b4 C: M! W1 P$ f
Experimental sampling, 试验抽样8 P2 c. k+ f9 n1 D2 G @. h
Experimental unit, 试验单位; {. C$ o' @# ^2 Z
Explanatory variable, 说明变量4 a8 E! Z/ g$ j
Exploratory data analysis, 探索性数据分析8 v/ |$ D. v, f( |3 r! d2 j7 N0 D
Explore Summarize, 探索-摘要
- Y* @* S/ v% D( L, @% o1 f5 yExponential curve, 指数曲线! G! Y V: P) L& g7 O5 I- u
Exponential growth, 指数式增长9 w, p$ b7 o4 e- j& K3 ?, r. @; ^# i
EXSMOOTH, 指数平滑方法 e h9 w' @0 `& q! P8 _+ K, w( a4 H
Extended fit, 扩充拟合
4 t, H2 }3 R* C. x) J+ ?Extra parameter, 附加参数) w5 `1 l* k1 r8 G
Extrapolation, 外推法1 p% c. f* i4 L4 h; N2 R: d7 E
Extreme observation, 末端观测值0 X7 Q& G7 Z8 P" v9 O0 X- i) K! X
Extremes, 极端值/极值1 T# V7 H" Z# @7 C# i& X
F distribution, F分布
- G* {0 r6 ^4 J! G4 C& W. MF test, F检验. C4 t& [' }3 r Z7 `
Factor, 因素/因子, ?; c$ V5 o4 ]& P
Factor analysis, 因子分析
* I+ Q: Q" w- Y6 a O! `/ k+ E YFactor Analysis, 因子分析2 [1 j: i) L; C5 d u
Factor score, 因子得分
3 e# {+ v. Y( r1 V1 s' |Factorial, 阶乘
' b0 u7 J& c" }$ @1 h6 UFactorial design, 析因试验设计
- V- L' p! s4 H( ZFalse negative, 假阴性* F+ |+ v4 p% h) `
False negative error, 假阴性错误
9 U7 l: H0 ^1 i8 ^5 d- X& O! tFamily of distributions, 分布族
! P5 o+ F' F- v' h' a- pFamily of estimators, 估计量族
$ n: z z% C% d! n! j# }; DFanning, 扇面0 E" y, {* k/ f" c" ]
Fatality rate, 病死率
5 p# [1 o) x- H! }. A, |! eField investigation, 现场调查+ U z2 m, s+ f {
Field survey, 现场调查
9 `& F; e, a9 v0 F# F/ C' XFinite population, 有限总体8 }5 y( @+ O) h6 l" k
Finite-sample, 有限样本
8 [+ U) V8 h6 s! M" J yFirst derivative, 一阶导数( w5 N' G0 N, y& A
First principal component, 第一主成分0 [( p& T% e& D
First quartile, 第一四分位数( K3 Z. M9 q3 I& K2 P
Fisher information, 费雪信息量7 ^6 u" y# J% G. X
Fitted value, 拟合值( _, E) H$ c D
Fitting a curve, 曲线拟合3 m7 J, H- C( B: U" |8 }! B
Fixed base, 定基' l# B4 \2 F8 i5 y
Fluctuation, 随机起伏: F1 e) }' H5 a6 F
Forecast, 预测) ?" w. ~1 c. G
Four fold table, 四格表
7 R+ u8 s: h$ o0 b C# i7 K4 DFourth, 四分点; b+ x* \- T( n2 P
Fraction blow, 左侧比率) [9 p5 ^# z u* O
Fractional error, 相对误差
3 K3 l. e1 ?+ G! |Frequency, 频率4 E* G. I Z5 C1 v
Frequency polygon, 频数多边图
. m) n% ~. @4 U3 t3 BFrontier point, 界限点; S6 u7 J# o$ n1 w& o
Function relationship, 泛函关系3 J m( D% l9 ?1 o6 j
Gamma distribution, 伽玛分布
" M6 q! x2 ]; p( X, ]* l+ jGauss increment, 高斯增量: I* C+ C4 d$ s! r; O
Gaussian distribution, 高斯分布/正态分布
7 c1 ?1 a% k2 q% M. XGauss-Newton increment, 高斯-牛顿增量1 z+ x* g" H8 i5 g' l6 q
General census, 全面普查
# T0 W& v+ M, L! A0 h' GGENLOG (Generalized liner models), 广义线性模型 $ V. I: @: ^) T7 [
Geometric mean, 几何平均数. ~4 e. ^" m* a2 t
Gini's mean difference, 基尼均差+ Y: i' A4 [; e/ w2 ^1 ]: U
GLM (General liner models), 一般线性模型
7 V1 Q O- C& ~0 P; W* r$ D- \' J3 ^! ]Goodness of fit, 拟和优度/配合度( H- k9 C' _" s: Z! `( \$ a
Gradient of determinant, 行列式的梯度
6 K1 a# D( g3 yGraeco-Latin square, 希腊拉丁方
! {7 L* ]( Q q( ZGrand mean, 总均值
8 L6 S3 j; |: p! P/ t |" SGross errors, 重大错误% z1 H& v7 z0 J+ h
Gross-error sensitivity, 大错敏感度
7 n/ B2 n0 ^' l+ B3 C6 EGroup averages, 分组平均
4 i( L9 r6 a% Y; g7 i% U, OGrouped data, 分组资料5 l$ w5 t( G) B6 K5 N
Guessed mean, 假定平均数
8 U$ q; K: v' R0 t+ a* V) \Half-life, 半衰期& q4 `& K! ~7 A
Hampel M-estimators, 汉佩尔M估计量 k8 v# c3 \. f+ `9 t1 R
Happenstance, 偶然事件' x" v/ m; t7 S: O) W/ f
Harmonic mean, 调和均数' j) l1 T- I/ W! M. ?/ N, a% T
Hazard function, 风险均数% a& L5 d1 M5 S: S- J, i
Hazard rate, 风险率
$ z1 p F; o7 N. {, t1 rHeading, 标目
* l$ h* i* A. V; N6 L) UHeavy-tailed distribution, 重尾分布
4 O b' o q) V! @+ s F( iHessian array, 海森立体阵
+ k( {8 d, @. |3 d& ~* ZHeterogeneity, 不同质
0 `, a. R; m/ }& c- [ ?- gHeterogeneity of variance, 方差不齐 2 K. R/ x8 H; F# l5 z8 Z* c! d& a
Hierarchical classification, 组内分组7 f c4 Q2 p7 L% h T
Hierarchical clustering method, 系统聚类法
2 Q0 k$ [6 t- e8 m2 y7 VHigh-leverage point, 高杠杆率点
2 n* }- K8 Y" G5 Z4 mHILOGLINEAR, 多维列联表的层次对数线性模型 E- {3 s$ `9 x. y9 @" d
Hinge, 折叶点
- t9 `1 a4 M- s# b+ A: tHistogram, 直方图
% W7 r4 E6 Y0 ^% B1 T$ @5 |Historical cohort study, 历史性队列研究
; y7 v" y5 R* y! L( PHoles, 空洞. N6 \- S' j8 M; l. B6 O
HOMALS, 多重响应分析% }+ C, W: R' p; j9 n
Homogeneity of variance, 方差齐性
3 @7 @3 S9 v' z. ~* Q1 O9 L" DHomogeneity test, 齐性检验+ f4 v4 \5 L( Y! Y5 S
Huber M-estimators, 休伯M估计量
3 O' B3 O7 r5 U5 x( o( o" JHyperbola, 双曲线
/ U+ i, j. c* z9 nHypothesis testing, 假设检验& V6 V2 E: ]- |; p0 Y8 f5 \
Hypothetical universe, 假设总体
3 [4 N) F; J$ m& xImpossible event, 不可能事件6 D8 {# X# o3 Q# m; m
Independence, 独立性8 }' k4 {2 n# C
Independent variable, 自变量
- s: L/ d( n8 Y, nIndex, 指标/指数
' Q2 m: W6 }9 |Indirect standardization, 间接标准化法0 i; _; u6 ~: ?3 p* T6 `
Individual, 个体0 S' p* S: e# ]+ H
Inference band, 推断带
8 ]5 ]' ^; b( }- `Infinite population, 无限总体. K' ?3 f3 g0 C" K
Infinitely great, 无穷大! Z+ w; P% J3 E4 j7 e7 T6 ~# _1 l
Infinitely small, 无穷小* G; m* t: Y6 | g" B
Influence curve, 影响曲线, d. j# y$ E/ [7 Z' b2 d. S
Information capacity, 信息容量2 ]6 r) c- E5 H1 y5 _- Y+ X
Initial condition, 初始条件
: [- |, U6 K1 [+ V$ _Initial estimate, 初始估计值
9 a9 q" C% Q( z1 C$ E9 a- dInitial level, 最初水平( K; b0 C9 I. k* n" p
Interaction, 交互作用; ^2 D( b) E9 O1 q8 V& b
Interaction terms, 交互作用项# p& Z2 k4 I! C/ M' @, P
Intercept, 截距7 L9 f( S4 S6 s8 K8 B- }
Interpolation, 内插法, c$ \; A$ W. @6 w
Interquartile range, 四分位距& ]0 E" z$ D) X4 m( t X
Interval estimation, 区间估计
# G; F: y' x$ `+ E' wIntervals of equal probability, 等概率区间
" s+ G2 {( Y6 o2 `& @) rIntrinsic curvature, 固有曲率4 p: l1 H5 p1 f3 ^0 B2 t" G
Invariance, 不变性
, k+ {2 @% l( }) V! X' eInverse matrix, 逆矩阵
) D3 M) E2 @0 Z5 K* w& u) lInverse probability, 逆概率3 P- [# T S, p+ P6 u8 L9 D
Inverse sine transformation, 反正弦变换+ c3 z- V- j) N0 S/ i
Iteration, 迭代
; c# N: E) d: M% d7 _Jacobian determinant, 雅可比行列式. i* G4 T/ d/ a Y- _9 V; {
Joint distribution function, 分布函数
f9 W! k6 N! {- i- m6 y( HJoint probability, 联合概率
4 ^8 x2 V# Y0 o$ r% PJoint probability distribution, 联合概率分布
+ R0 G. ~. R% d. Q+ ^7 F) LK means method, 逐步聚类法8 r; p5 F9 U4 Y: p0 k4 I1 B
Kaplan-Meier, 评估事件的时间长度 : b0 [$ K U) \- F: v2 V8 C$ Q. L1 j
Kaplan-Merier chart, Kaplan-Merier图
& [2 }1 \; N3 AKendall's rank correlation, Kendall等级相关9 F! s; p3 |8 |, r
Kinetic, 动力学
; l9 `3 N! J; RKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
; B( b* i* Z, B+ e7 |' K0 P. uKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 H, I& T: a6 q! u, c% k
Kurtosis, 峰度
) B; @% z; G0 y5 }+ s; ]: jLack of fit, 失拟8 y) w3 d) M( b
Ladder of powers, 幂阶梯
2 \, ^! L' ?# [; A* z& OLag, 滞后
! Z) X% ^9 P4 Z' g9 u3 g9 ^Large sample, 大样本1 F( r$ I, v! M; r- l+ p
Large sample test, 大样本检验; b. v; C6 B# j/ [% Q o
Latin square, 拉丁方
+ I* _; H$ i" t1 [2 y: @Latin square design, 拉丁方设计
6 h( |' J! n$ { M4 _4 p4 MLeakage, 泄漏
& N, A* |* K% ~* k! }Least favorable configuration, 最不利构形% ~ g6 m- x- k) c) \- N
Least favorable distribution, 最不利分布
6 ~% R# K& r8 O+ j! A- PLeast significant difference, 最小显著差法
, k$ i1 m3 C0 r" [Least square method, 最小二乘法8 |8 X% Y3 F" ?- M6 r
Least-absolute-residuals estimates, 最小绝对残差估计( [, l: u( t) ~: {" O4 J
Least-absolute-residuals fit, 最小绝对残差拟合2 A- v8 z# S( D! N4 t; E' c$ d
Least-absolute-residuals line, 最小绝对残差线6 G8 C) q$ {0 r+ l- f8 Y; a4 E; E- _
Legend, 图例, @" d! h9 d) ^. n
L-estimator, L估计量
& w) l( K# {; r" i5 yL-estimator of location, 位置L估计量: h- W4 f% ]3 j* A2 ~6 K! W
L-estimator of scale, 尺度L估计量1 J$ D9 t0 h% d( A6 E- l
Level, 水平7 i+ ~: r5 @2 G) ?* Y% a
Life expectance, 预期期望寿命
8 Y) u& @5 a7 ]6 b5 g+ Q% bLife table, 寿命表
; l, C( ]. b2 _/ ` V5 @; \Life table method, 生命表法
: y3 D; S X0 J0 T! ZLight-tailed distribution, 轻尾分布
+ {9 A# s2 n* R4 G# {- gLikelihood function, 似然函数' d& {: q; n+ z( N+ E; X
Likelihood ratio, 似然比' x* T$ K3 n- a2 g# I: q
line graph, 线图0 Q2 M. Y* @( U
Linear correlation, 直线相关
. }: ?' F6 M; Z" U0 K# {0 VLinear equation, 线性方程
' R0 E. S* p) v5 lLinear programming, 线性规划; h2 E0 W$ l4 h3 A0 Q A! q' Y
Linear regression, 直线回归8 E8 q8 c5 ^- J- H
Linear Regression, 线性回归( c- \( S# k$ n" d0 }) B3 x; V4 V
Linear trend, 线性趋势
$ k% w V' N: h5 `: ]. jLoading, 载荷 ' d( o: w5 `* D) h
Location and scale equivariance, 位置尺度同变性; }; w* e, f1 ^* b% t
Location equivariance, 位置同变性
( _' ^3 m3 j* C, \; r- K9 sLocation invariance, 位置不变性
) q: ], Y6 L+ LLocation scale family, 位置尺度族) a9 }8 M9 m! v$ Y$ r
Log rank test, 时序检验 K7 k& L5 V4 n l0 j! S n. a
Logarithmic curve, 对数曲线
+ n$ H7 e% {% NLogarithmic normal distribution, 对数正态分布
' I) q( R- C2 j2 B+ wLogarithmic scale, 对数尺度7 V9 Y3 E% s, V) J% s# x
Logarithmic transformation, 对数变换
* |7 y4 R- e8 M7 I; A/ |Logic check, 逻辑检查
, T! h- @0 ?/ V- ]- {9 wLogistic distribution, 逻辑斯特分布
! q4 H# I4 _& L' }1 V YLogit transformation, Logit转换
* F/ N* s3 [4 M1 E$ E9 WLOGLINEAR, 多维列联表通用模型
+ L S, D% [- H; V# E* J' oLognormal distribution, 对数正态分布( c! F2 C+ T) b# y
Lost function, 损失函数8 o7 |- x* O) G* `1 u
Low correlation, 低度相关" s# m, d+ d; J1 ?0 [: W
Lower limit, 下限
) p0 r8 W8 E2 _ H X9 D$ C5 | zLowest-attained variance, 最小可达方差
$ F, r+ ~+ s- t- x( G3 l/ W. YLSD, 最小显著差法的简称
. i' i, H: f, q6 [Lurking variable, 潜在变量
$ Q, k! h* P# W- jMain effect, 主效应- k9 C3 J" j$ f' [3 R) K+ S! p1 U
Major heading, 主辞标目
3 G: q% N9 w2 \# @# V2 ~Marginal density function, 边缘密度函数3 p8 N2 E/ J8 e1 w
Marginal probability, 边缘概率
/ `. ]6 J3 ?9 aMarginal probability distribution, 边缘概率分布
7 B: e0 I2 [ a3 T3 h8 TMatched data, 配对资料
5 p- D# q, H$ l4 x, IMatched distribution, 匹配过分布1 z& |1 B4 {2 Y' ?9 i9 [/ @
Matching of distribution, 分布的匹配
$ b, L8 U3 w5 o+ r* bMatching of transformation, 变换的匹配7 A) H7 V* ]7 J# }2 x
Mathematical expectation, 数学期望; x! s' U3 @( l" l% c0 h& v) r
Mathematical model, 数学模型7 P+ W1 |0 j4 s$ H' Z+ z' [
Maximum L-estimator, 极大极小L 估计量
1 Q% k) }' f0 x6 i% u# c e9 w9 P% `Maximum likelihood method, 最大似然法3 R6 Q% X0 c4 K. w* d
Mean, 均数
, V' x' I ^' O' E" v) QMean squares between groups, 组间均方
6 w8 H/ J5 }/ q+ y4 N% [Mean squares within group, 组内均方8 a( {2 O! O2 g5 p
Means (Compare means), 均值-均值比较/ ]/ R2 ~9 t2 {# {2 U* I6 C
Median, 中位数
$ W& g+ X" A) {* u( o- YMedian effective dose, 半数效量& E- U5 [# u9 I( f1 ^% {
Median lethal dose, 半数致死量1 M% Y* o! b! e9 ] e! r
Median polish, 中位数平滑
$ T& E% \3 F0 O( g. i% f' rMedian test, 中位数检验: s1 ?& l9 y" V( r
Minimal sufficient statistic, 最小充分统计量
! O4 R4 z7 ^) q0 ]( C4 lMinimum distance estimation, 最小距离估计- w* E- M& T5 h. _8 V
Minimum effective dose, 最小有效量. h. w4 _7 F( O f/ ]0 [
Minimum lethal dose, 最小致死量& m% n6 L8 ~$ J7 d
Minimum variance estimator, 最小方差估计量
% X1 I, {8 x. s) ? hMINITAB, 统计软件包8 r" [; p- ]# Y4 j( f
Minor heading, 宾词标目* p; u8 q; i1 _4 {9 g: ~9 \
Missing data, 缺失值
" v4 X! q% s$ |* v7 N% e" [Model specification, 模型的确定! z% [1 M' e6 M/ N- B1 n" B7 L, l
Modeling Statistics , 模型统计$ @8 s0 @" m% X( E0 M
Models for outliers, 离群值模型! Z5 U3 \* X9 h& y h: G, n% d* @
Modifying the model, 模型的修正
4 Y. J$ B: ~& H6 xModulus of continuity, 连续性模& l2 k/ v3 q9 ~/ s
Morbidity, 发病率 0 M7 x8 t0 K6 @/ k7 l7 m* b3 a: P: S
Most favorable configuration, 最有利构形8 m: `2 v- h4 R) t1 z1 R
Multidimensional Scaling (ASCAL), 多维尺度/多维标度" c- p2 L9 L/ O4 b# h1 A8 Z8 E+ C, e
Multinomial Logistic Regression , 多项逻辑斯蒂回归0 s, r6 J) L: J$ X, `4 {+ a
Multiple comparison, 多重比较
4 H/ q* e' l% ]2 Q* AMultiple correlation , 复相关
; w7 p. K5 O1 a8 s* x, m7 EMultiple covariance, 多元协方差
" I- c/ z, l9 b3 bMultiple linear regression, 多元线性回归
( z& g0 u. g1 j( n/ U; SMultiple response , 多重选项
2 K: ]2 g9 G+ Z; }Multiple solutions, 多解3 P& H& F- q: r* r, i# U
Multiplication theorem, 乘法定理- s# p6 m. Z0 L1 [9 R. v: @1 N3 x
Multiresponse, 多元响应# n. r6 A l! h: c4 ~" z* V
Multi-stage sampling, 多阶段抽样" N/ c( e4 f9 V% V; R9 N
Multivariate T distribution, 多元T分布
) F J+ a' g- ?Mutual exclusive, 互不相容4 }( I/ A9 X) j0 w- m1 H
Mutual independence, 互相独立9 n& g: p6 E$ [0 y! @
Natural boundary, 自然边界- I+ d% h% x2 ~! }9 G% h9 E
Natural dead, 自然死亡
' A6 v# r6 d7 F6 XNatural zero, 自然零
& u2 R. B7 V) M' h9 Q: j& dNegative correlation, 负相关0 J+ l* f; e8 o, y) O- K$ t
Negative linear correlation, 负线性相关
% ^6 u, i7 y' q( R$ g3 N& ENegatively skewed, 负偏
5 ]# ]$ o ^+ i0 Q" ^Newman-Keuls method, q检验
) b" [8 f7 L3 ]; @/ zNK method, q检验1 H) l: q: [0 S w3 l) H) U$ q
No statistical significance, 无统计意义
" ?4 W, Z1 _1 U. iNominal variable, 名义变量
6 c/ k, O+ X8 x* F: S8 TNonconstancy of variability, 变异的非定常性
# X6 S1 x3 ]5 v3 GNonlinear regression, 非线性相关
4 [8 U1 e$ {$ I4 _Nonparametric statistics, 非参数统计
% n7 q; n$ _0 b r' E7 {Nonparametric test, 非参数检验
2 n' T) I% X; U& W; t7 BNonparametric tests, 非参数检验' I" n8 t( H0 T
Normal deviate, 正态离差/ S' Z: n5 V7 |, F, n! H6 O: O
Normal distribution, 正态分布
: p! p2 [, N3 z' MNormal equation, 正规方程组
8 G2 U7 i1 ~5 p5 l8 uNormal ranges, 正常范围: ^2 I; @: w# \6 m. @# \
Normal value, 正常值
( i( D, `/ W2 W7 t: u: oNuisance parameter, 多余参数/讨厌参数
* t2 B% \$ M8 E4 j! dNull hypothesis, 无效假设
$ Z* \. |6 k" L# a( i5 DNumerical variable, 数值变量
/ T5 \5 ]+ j$ s' b4 ~# JObjective function, 目标函数7 b5 e( j) R9 ~) D
Observation unit, 观察单位
; S: n8 `4 y6 X. {) u9 f) y/ \1 nObserved value, 观察值9 Q/ ~1 B8 }4 U
One sided test, 单侧检验
0 e! x8 q1 Y& _1 fOne-way analysis of variance, 单因素方差分析+ K& N1 S. p7 n2 T
Oneway ANOVA , 单因素方差分析( `: l4 L' M6 ]% [
Open sequential trial, 开放型序贯设计7 K4 l2 _, J x6 U' [4 b
Optrim, 优切尾
' m5 b R$ g2 yOptrim efficiency, 优切尾效率
6 I+ d8 u+ n; f0 B; YOrder statistics, 顺序统计量
8 i# v$ G0 d1 e- ^/ XOrdered categories, 有序分类
5 }, J! b- Y/ ^: Y3 D- o0 k, JOrdinal logistic regression , 序数逻辑斯蒂回归! K& [' p3 L9 @8 |& g
Ordinal variable, 有序变量) [. v, t1 ^* p! c
Orthogonal basis, 正交基7 D3 o, [' ?3 D! W
Orthogonal design, 正交试验设计
# T. u4 n i* I% ?) k `0 @+ l7 MOrthogonality conditions, 正交条件. ]/ z# `! F7 s% ] j4 m+ a
ORTHOPLAN, 正交设计 8 }$ v/ t! {! U( \4 l+ m
Outlier cutoffs, 离群值截断点 I! `4 Z3 X4 _# Y5 T1 e
Outliers, 极端值8 {: Z6 Q* k) N9 A
OVERALS , 多组变量的非线性正规相关 D, {3 o* ?1 b; G
Overshoot, 迭代过度
7 b% G" ^& p H) [; n4 w1 w! ~0 pPaired design, 配对设计: e4 u2 e! R" m# I5 | I! x' p3 @! M% x
Paired sample, 配对样本0 Q6 \# v5 [5 `' g
Pairwise slopes, 成对斜率! i1 z9 j7 @. j
Parabola, 抛物线5 j; I/ R$ _7 z: f
Parallel tests, 平行试验% q9 t& d" C% C# f9 M: U
Parameter, 参数
4 ~0 w# a! u* J0 t7 t' oParametric statistics, 参数统计4 D' T* U8 n6 o$ D! t% Q) {; y
Parametric test, 参数检验
& G2 m" I( \0 ^; ~3 \9 m* v, EPartial correlation, 偏相关, g4 t5 a0 c/ g! s4 m
Partial regression, 偏回归2 C2 Z/ u p' t2 W2 U2 X" J
Partial sorting, 偏排序( f& r. i$ y l9 |; c
Partials residuals, 偏残差
* z! G. M& m% n8 OPattern, 模式
5 c: g: j' x$ NPearson curves, 皮尔逊曲线6 S' {2 B8 ~# R" {- g
Peeling, 退层
/ O9 V7 D! C6 M- P1 rPercent bar graph, 百分条形图
; r/ \# v8 N6 \9 ePercentage, 百分比
% `+ P2 A- i* SPercentile, 百分位数% X& W* u5 N8 x4 m8 p
Percentile curves, 百分位曲线
% J4 E0 W/ G( G. l$ KPeriodicity, 周期性3 D y6 e2 g+ ]9 {) j8 p! U
Permutation, 排列$ F. z: @. o" P4 e
P-estimator, P估计量" l4 R# |9 A+ I& ?7 k' W% a
Pie graph, 饼图
* n0 c0 u! t" S3 MPitman estimator, 皮特曼估计量4 b1 D) v/ x0 ^4 \% {
Pivot, 枢轴量: q1 v3 ~1 D9 h A' p5 k! k4 d9 Z
Planar, 平坦
y1 J- B8 O2 nPlanar assumption, 平面的假设: s M x1 Z; ]& w* j8 y- o7 S, p
PLANCARDS, 生成试验的计划卡
1 Q- g( _& n5 B5 R0 wPoint estimation, 点估计
6 E! f, T+ H. MPoisson distribution, 泊松分布" l4 S; P8 j7 z( E, m% V
Polishing, 平滑
( b* i( U0 |& R" d" D9 v1 tPolled standard deviation, 合并标准差
o2 V0 ~7 C+ PPolled variance, 合并方差
0 ]' N4 Z; ]; R. pPolygon, 多边图; T* Y1 X7 a# B! r* b; a P4 W8 s! O
Polynomial, 多项式: ]" A3 J0 O3 h7 {" ~. _, l- X; V& G
Polynomial curve, 多项式曲线5 i: {' t& b" ]; p
Population, 总体2 V* t- ^$ R$ x- z# l$ y; X, Y3 _" j
Population attributable risk, 人群归因危险度1 g2 ~6 C9 X& Q' X% B. y
Positive correlation, 正相关
( N8 t: _# }- G8 MPositively skewed, 正偏# v/ n' L, i8 E. a6 Q. [
Posterior distribution, 后验分布
% F4 K% B3 C3 Y$ s2 JPower of a test, 检验效能* ?& T# J3 c7 t4 w# T
Precision, 精密度
# d; P" z1 _7 N8 ]0 l) s( OPredicted value, 预测值: Z2 M8 F0 i" A. ~! e' H- }& A6 o
Preliminary analysis, 预备性分析$ R8 l R1 p1 x5 }9 }! u" y
Principal component analysis, 主成分分析
6 Q! {" C3 c1 T: o* tPrior distribution, 先验分布5 c( P1 p) M) t$ a. f8 {+ Y7 M
Prior probability, 先验概率
2 a. p5 A' n+ T- `# `Probabilistic model, 概率模型0 w$ i6 w1 A" g5 n( l* A
probability, 概率* L5 d* J0 H! w, [8 d$ i; |1 f/ ]
Probability density, 概率密度' N% W o+ @! k) G+ x J A% d. I
Product moment, 乘积矩/协方差
/ g7 `$ |( `4 P% f7 CProfile trace, 截面迹图
6 f4 H L3 U; ^+ w( a9 FProportion, 比/构成比# C& F0 ?3 L5 J' ^3 y' ~! J3 K
Proportion allocation in stratified random sampling, 按比例分层随机抽样
: Z2 B# ]0 ?7 R6 u8 O2 j/ n4 sProportionate, 成比例
6 b% @9 ^+ f5 C+ U8 VProportionate sub-class numbers, 成比例次级组含量/ ~" v3 D, {1 s
Prospective study, 前瞻性调查
% e; v/ i; x6 lProximities, 亲近性 ! T2 r/ d1 h8 Q, s
Pseudo F test, 近似F检验
3 v; W# v. U1 {2 K$ pPseudo model, 近似模型, A8 K: d) c1 p: T4 L3 w' i0 P3 {
Pseudosigma, 伪标准差( _$ h0 J7 L {7 O
Purposive sampling, 有目的抽样' k' ~9 J v' V. \' e, |8 Z
QR decomposition, QR分解
' J, G3 [: }1 @7 m* YQuadratic approximation, 二次近似
' E, T% z& d+ p$ k( H- P' [Qualitative classification, 属性分类
; l+ j: y. @$ _; w+ @1 P1 oQualitative method, 定性方法
/ H; h$ ^) e% rQuantile-quantile plot, 分位数-分位数图/Q-Q图
2 A" o& X* H8 R9 l1 l7 GQuantitative analysis, 定量分析
8 H/ k1 Z) y7 _0 xQuartile, 四分位数
( M: h2 E$ R- aQuick Cluster, 快速聚类
! w( `" r6 n- L7 c' o/ i* {Radix sort, 基数排序
, Q: g) v) x3 d( D: ]/ NRandom allocation, 随机化分组
; `+ s9 q% ^: c2 \Random blocks design, 随机区组设计. u% |$ P# [9 k- e& u9 [% V) L" ~
Random event, 随机事件
8 ]; X0 e' D2 z& @3 `1 bRandomization, 随机化! L" J6 E9 I9 \4 P$ e( o
Range, 极差/全距' p) z$ d, {: K7 t! [
Rank correlation, 等级相关: X# b' h7 a R1 T
Rank sum test, 秩和检验" b S/ c: g8 i( q- I$ j, r' S
Rank test, 秩检验, O5 u% y! a* h2 R- V) P
Ranked data, 等级资料
) K% H& y( v, C X S2 mRate, 比率
: |% d; f* ^' D% w2 rRatio, 比例
/ F) H% T* H" i& PRaw data, 原始资料
7 ]* p8 H0 M+ k( c& |7 lRaw residual, 原始残差
& I% ~& Z/ X2 h! f4 f5 _Rayleigh's test, 雷氏检验& e" r) d! J" p, G- Y
Rayleigh's Z, 雷氏Z值
! w7 ?$ j/ d/ I8 Y; p, O" pReciprocal, 倒数
0 P7 }2 z5 s' C- A: c# gReciprocal transformation, 倒数变换# G3 |2 V& b. A
Recording, 记录
3 B& d0 E5 k8 X, I( \+ F/ mRedescending estimators, 回降估计量0 n6 ]- c1 Y. t9 M. n u; N+ V
Reducing dimensions, 降维3 j* \' ^% [5 y2 s) }
Re-expression, 重新表达
8 V; \" a. t. }Reference set, 标准组2 P$ u7 q# w: A: k0 o
Region of acceptance, 接受域
! d# @$ s) I6 fRegression coefficient, 回归系数
0 B( m. d5 U6 n% _7 XRegression sum of square, 回归平方和
" F) { T2 [- v# ?4 a6 z; RRejection point, 拒绝点
% o7 \" T2 B- A) W& {2 _0 P8 A0 ZRelative dispersion, 相对离散度# d6 [7 J4 [* C) Z6 A
Relative number, 相对数 {9 R% F6 n! e* w0 u3 E
Reliability, 可靠性
# @) Z) _/ G5 i( k* I( pReparametrization, 重新设置参数) X ?. @' C9 g( [$ k9 u& ]! k: e
Replication, 重复; C/ n0 X0 K- T, @4 L3 C% k
Report Summaries, 报告摘要
& u6 Q: Q7 k) D, L1 dResidual sum of square, 剩余平方和: D) z6 ~9 d! w: d' J
Resistance, 耐抗性
' \! s8 X) S$ W3 WResistant line, 耐抗线8 T% R* T3 Z. o
Resistant technique, 耐抗技术. v& [3 b' r4 j2 |5 a+ D/ u
R-estimator of location, 位置R估计量: u6 b# B' P. \ d
R-estimator of scale, 尺度R估计量' M. H6 X; p2 d+ P
Retrospective study, 回顾性调查; X7 f+ n% ^3 u g, N# i6 s* [+ }' O
Ridge trace, 岭迹
( ~1 Z+ v) h, TRidit analysis, Ridit分析9 I# u5 x, L3 h% `7 K! o; y) Y& \2 p" ~# k
Rotation, 旋转
) `) H9 E# B: |: D$ H1 bRounding, 舍入3 B+ S }7 r2 [% y4 R9 x
Row, 行
3 _; B0 f ~( a' r1 `Row effects, 行效应
( @5 t) [0 R7 s# e$ l! wRow factor, 行因素4 c. \% W9 i5 c/ I' Z
RXC table, RXC表, b8 m. L; @ n
Sample, 样本( X. h. r+ w: y5 r9 M
Sample regression coefficient, 样本回归系数
9 T, k3 R0 K7 i) lSample size, 样本量/ P, u5 C1 o4 z f1 n% l! o
Sample standard deviation, 样本标准差
8 `- V8 M5 Z1 [& e6 ?4 [6 s) V0 U; hSampling error, 抽样误差
- k4 E+ [! t7 B: eSAS(Statistical analysis system ), SAS统计软件包4 }) z: ~$ T# s
Scale, 尺度/量表
2 S0 l7 ~0 P/ A0 k" n; uScatter diagram, 散点图: D+ O1 P3 I* ^) U6 V$ p( K2 K+ C4 k6 `* @
Schematic plot, 示意图/简图3 h+ `9 \3 X7 N2 Y' {
Score test, 计分检验8 P1 Q2 t" \. v |8 p
Screening, 筛检
: F; b# @- ?& ~* aSEASON, 季节分析
6 T* n/ M: W$ d9 M! |Second derivative, 二阶导数5 s' C* h0 B Z! O3 [( x9 S3 Z9 T+ _
Second principal component, 第二主成分7 e; K5 ^. V3 L" M0 H9 f6 z
SEM (Structural equation modeling), 结构化方程模型 r% T0 F3 V1 I( u; w2 Y+ ]
Semi-logarithmic graph, 半对数图
+ O' h2 {3 s6 L9 w# B' B- OSemi-logarithmic paper, 半对数格纸
1 m( m$ K4 X" E1 h2 fSensitivity curve, 敏感度曲线6 z# s7 s( y' q) @7 Q$ O
Sequential analysis, 贯序分析
( `& L5 ]* l$ U8 I/ r0 ]Sequential data set, 顺序数据集6 v$ `8 G6 g* a; a. v" A
Sequential design, 贯序设计
4 K, {8 n# C6 J* m2 C: X" k. H0 TSequential method, 贯序法" c7 o" u8 A8 w, l
Sequential test, 贯序检验法
}; k) s1 K9 H* h% U) cSerial tests, 系列试验
+ D2 U& W8 d8 u2 WShort-cut method, 简捷法 $ R2 `# t; D0 M- ?0 L1 B8 a
Sigmoid curve, S形曲线
3 _& w$ W3 W2 I. l' L1 x9 fSign function, 正负号函数
6 t. j2 R5 \+ w$ ?' q' XSign test, 符号检验
8 u" O8 d: |5 @" ?, ^Signed rank, 符号秩4 ^5 v: t- I2 v# g; a( u- R8 K# q
Significance test, 显著性检验
m* y0 {. q/ I+ v, ]. `5 d: uSignificant figure, 有效数字 x- T" x U# o) ~% O" E, Y% W
Simple cluster sampling, 简单整群抽样
6 v3 N: _* d# j& X% O* I; uSimple correlation, 简单相关
5 Z% Y+ W3 u0 u' g ?3 t5 O: q& CSimple random sampling, 简单随机抽样/ U! E+ _ Z# E6 _, M0 D) _( T
Simple regression, 简单回归
5 ~! E1 w4 B" G" bsimple table, 简单表
- \; \0 B {5 r nSine estimator, 正弦估计量2 N W) z; g8 v. e* u, I
Single-valued estimate, 单值估计
- q/ N" G) U6 q9 Z I3 f; k8 Y+ A, Y8 nSingular matrix, 奇异矩阵
" t& p7 w9 `, G. g& \: d$ _Skewed distribution, 偏斜分布0 k# t) W! ]5 f( o) o
Skewness, 偏度
4 @7 y, g7 Z" b; ^Slash distribution, 斜线分布
: L3 X0 c, X+ o" e, ySlope, 斜率
8 P1 {3 s. h0 q6 R! o2 pSmirnov test, 斯米尔诺夫检验1 v W8 y+ \9 q) C
Source of variation, 变异来源
$ b9 x; t# H3 LSpearman rank correlation, 斯皮尔曼等级相关. ~& `9 f2 `! {* f. W
Specific factor, 特殊因子7 w: T* r& Z% L3 l
Specific factor variance, 特殊因子方差
3 ~7 X% |- A( K9 _: }4 G5 k2 v4 x* WSpectra , 频谱# ~& O6 }* q/ K: ?9 g
Spherical distribution, 球型正态分布
# \3 M5 `/ c) T% B6 b5 j+ A4 ^Spread, 展布/ y& c! d' q) t v# S2 A: E F
SPSS(Statistical package for the social science), SPSS统计软件包( `) G0 Z/ |+ S
Spurious correlation, 假性相关
9 A8 B) _( @7 Z0 O0 U' }7 MSquare root transformation, 平方根变换
* p! N& X ~1 E( T9 }Stabilizing variance, 稳定方差5 {7 K* o. D) z# I
Standard deviation, 标准差) y! }1 M/ V8 G2 J! a" O
Standard error, 标准误
3 u/ n, g( D- o) L- _Standard error of difference, 差别的标准误: Y% F. F- u' Q6 l, V9 Y
Standard error of estimate, 标准估计误差# m+ a! v9 D, M
Standard error of rate, 率的标准误& A/ {. ~$ U2 ?7 X- G8 k2 j8 g
Standard normal distribution, 标准正态分布
# n w9 e/ q. G) U3 k2 kStandardization, 标准化/ m/ L7 x; i( u5 S6 C5 T9 L
Starting value, 起始值
% C0 @4 {2 v y+ ^6 U' L qStatistic, 统计量
N- y" E9 u3 a6 d- R7 J9 ~) AStatistical control, 统计控制
/ _. ~$ `$ X, ?5 D$ F0 E( F: uStatistical graph, 统计图1 G! M# b4 O" |6 W) r8 y
Statistical inference, 统计推断: U8 }4 O7 y& \
Statistical table, 统计表3 ~( ]4 p# A$ X* Z1 V0 O
Steepest descent, 最速下降法
2 H$ J* I3 g u, ?7 R% g. @Stem and leaf display, 茎叶图
# ^! g6 W6 |4 n( U, i7 r9 YStep factor, 步长因子
0 c! [& I7 \$ Q' u) |: }Stepwise regression, 逐步回归% G5 v0 z) I, J# h* s2 |: S# u8 C
Storage, 存/ P+ n. p" f1 `" Q5 D# r: n1 {# G
Strata, 层（复数）4 ]/ @& P( ]; n: k0 r
Stratified sampling, 分层抽样
]( b$ N9 y, P$ ?8 H) ~Stratified sampling, 分层抽样
) ]! [1 J$ b- N1 BStrength, 强度
0 v. O& _6 B3 O0 S2 g- tStringency, 严密性) Y% b9 O2 i3 m" z1 ` c
Structural relationship, 结构关系/ m* X) ~" }5 J. p: s
Studentized residual, 学生化残差/t化残差) d& v0 c$ Q4 H @9 Z% o* H
Sub-class numbers, 次级组含量
# J& U( n3 w$ c8 }: `' y& oSubdividing, 分割
; G" I: _( f+ y" PSufficient statistic, 充分统计量; |% ^/ Y- Y: G4 q- D8 l, \) ~
Sum of products, 积和
6 u. ]& w) Z8 d" g2 y8 k# ^' ISum of squares, 离差平方和
# F2 b. G" K: x1 K/ z! c1 iSum of squares about regression, 回归平方和
/ y8 O& O1 `1 ASum of squares between groups, 组间平方和& N. E4 Y+ K6 k' r5 s
Sum of squares of partial regression, 偏回归平方和
0 g* m z5 m* `8 u& [9 tSure event, 必然事件% u; J) f0 }3 n& r5 U% F4 X
Survey, 调查
2 V o H) X4 g0 x0 X! `8 GSurvival, 生存分析. ~- }( k6 ^% ^; S, [# a
Survival rate, 生存率
% B3 O7 r- X2 n7 gSuspended root gram, 悬吊根图
( \6 ~. h7 \! M- [. f5 hSymmetry, 对称' ]- h; C- E7 A' E
Systematic error, 系统误差
g+ V @5 b% [) K/ ]Systematic sampling, 系统抽样' Y- R6 B# u! a; v
Tags, 标签% B# e7 s+ }7 H8 C
Tail area, 尾部面积
: j0 i- O" z* VTail length, 尾长+ s+ I( [7 d. O! E! }6 `. y* t3 M9 a
Tail weight, 尾重
; Y# I3 N, V+ q0 q i. G# GTangent line, 切线7 L6 f* U- e# B9 `- U" f! _
Target distribution, 目标分布
6 _0 Q4 N; t$ i) d3 c& ATaylor series, 泰勒级数8 a$ a. ~$ G7 ?9 m7 B$ Z5 A& `
Tendency of dispersion, 离散趋势
/ S, g5 Y, ^9 \+ s+ I, f" B7 g; ?Testing of hypotheses, 假设检验
* |6 c! H$ b0 K# D* e1 B, X3 O$ r5 |Theoretical frequency, 理论频数. \( g& E4 i+ P$ @
Time series, 时间序列
; G" _9 b2 Q4 e& H( FTolerance interval, 容忍区间
) z4 t8 s2 C0 a( x" Q$ OTolerance lower limit, 容忍下限+ E) {7 R& X8 R% D
Tolerance upper limit, 容忍上限2 q) w2 _* A2 T* U
Torsion, 扰率, l& U, y: X" f, O5 t; e. m
Total sum of square, 总平方和
5 o3 D* I( r2 y1 ]Total variation, 总变异
2 |$ D1 T& g! D7 FTransformation, 转换6 m, R$ Z7 ~% f" C/ d2 {4 S3 C+ K1 {
Treatment, 处理5 A! R! j- `, z% g
Trend, 趋势7 t- @3 k5 K3 d; n9 i* W7 u
Trend of percentage, 百分比趋势
% U) S( f5 H9 k$ a. l& h; w4 ETrial, 试验
h! h% L/ H9 e" ?" t' J) ATrial and error method, 试错法
! N9 m; b1 R# j Z( dTuning constant, 细调常数- M( l1 b4 E" _' |: Q" s
Two sided test, 双向检验
" }, Y9 A% R4 X3 k) L( \Two-stage least squares, 二阶最小平方! S+ F4 O- o& K7 P- j! \
Two-stage sampling, 二阶段抽样1 J) B6 l* D) l, {$ s. C
Two-tailed test, 双侧检验
7 {% m' u! y& C cTwo-way analysis of variance, 双因素方差分析: R. g; H% c" x7 _! }1 ?& L+ v% ~
Two-way table, 双向表7 T! q3 o( m* t) n( C6 O8 x, p7 A
Type I error, 一类错误/α错误- ^* n% T1 b$ G# v! u
Type II error, 二类错误/β错误
- j& f9 e# a3 r; C, g" o$ c0 FUMVU, 方差一致最小无偏估计简称2 e7 O% v7 r7 G. J2 m6 T+ L6 W
Unbiased estimate, 无偏估计+ N; p7 s! _2 A3 k% I- c
Unconstrained nonlinear regression , 无约束非线性回归& P" o( O5 T3 s% r5 \. u- Q
Unequal subclass number, 不等次级组含量9 g! H( J, U/ i$ {3 |8 V) E7 a
Ungrouped data, 不分组资料
/ A. D6 P7 |5 |" V! o- Y$ ^ `Uniform coordinate, 均匀坐标/ Z5 u/ \% ]; `: Z: C) G6 g
Uniform distribution, 均匀分布
9 q1 H" q! B7 B$ z9 ~Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
1 A `/ Q( a0 h- hUnit, 单元
# P Q8 U, K _! a5 f3 g! BUnordered categories, 无序分类
) X& B4 S: f2 e) G P- B4 i! B. BUpper limit, 上限
2 ?* \- B2 [8 S/ dUpward rank, 升秩 u' C, [1 o+ o- x v
Vague concept, 模糊概念
0 I& {+ }* S( R; R+ G/ A' \6 |Validity, 有效性 _; C, c9 X/ s4 Z8 F) {+ M7 J
VARCOMP (Variance component estimation), 方差元素估计
- M. A' w r2 h/ t% oVariability, 变异性& {! j0 ]* i& A
Variable, 变量7 w; W1 ]7 ?& m6 ?
Variance, 方差
, F ?! w& H" K$ j! K( V& {Variation, 变异
! @, n, f7 n7 Q9 h- ?/ {Varimax orthogonal rotation, 方差最大正交旋转
3 P# z4 ]2 v/ o$ Z6 jVolume of distribution, 容积/ T- B9 r2 w& D8 t0 o+ f
W test, W检验
7 D0 b' j; j, k- v( A+ v N r6 cWeibull distribution, 威布尔分布& g/ t* v8 q1 o- ~- k( A
Weight, 权数7 \1 G3 j+ T$ Z; d' P8 X; _. C
Weighted Chi-square test, 加权卡方检验/Cochran检验9 e2 ~ }6 \! m. s7 P" u# R
Weighted linear regression method, 加权直线回归
" r9 b! Z D3 J" Q8 zWeighted mean, 加权平均数' L6 A$ C5 K3 W9 a7 {* P
Weighted mean square, 加权平均方差3 q% A. O& @! E+ G( N( c
Weighted sum of square, 加权平方和- @+ x- t% y8 c: U
Weighting coefficient, 权重系数
8 R, D( m3 z6 H! J( d; FWeighting method, 加权法
6 [; L9 q4 B8 h/ _W-estimation, W估计量; b$ ]7 _8 `" J6 ?% v
W-estimation of location, 位置W估计量2 S. G4 }7 C' A- V) O: C
Width, 宽度' s' V r( q8 A
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
9 W. ^4 C2 F$ X& R$ ?Wild point, 野点/狂点5 q, U w: N2 t: l% _
Wild value, 野值/狂值
% ?5 B5 _" F7 x5 W' J0 pWinsorized mean, 缩尾均值+ F2 ?) }3 a, R& n/ o0 x4 E4 P7 Q
Withdraw, 失访 4 q/ U3 x" G' F x. G
Youden's index, 尤登指数5 R. u: f9 |2 L- ?
Z test, Z检验' C ?) w7 V* n* ?
Zero correlation, 零相关 t2 c7 K% B# @3 C; ]7 O
Z-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
